Triple
T509404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2 train |
E10571
|
entity |
| Predicate | usesSignageStandard |
P1739
|
FINISHED |
| Object | MTA subway route signage |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: MTA subway route signage | Statement: [2 train, usesSignageStandard, MTA subway route signage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSignageStandard Context triple: [2 train, usesSignageStandard, MTA subway route signage]
-
A.
signageStandard
chosen
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
B.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
C.
usesStandard
Indicates that one entity adopts, follows, or operates according to a specified standard defined by another entity or reference.
-
D.
hasBranding
Indicates that one entity carries, displays, or is associated with the brand identity of another entity.
-
E.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f164a9d48190b525a97b5c06ffe2 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edfe236481909901cc7d4281b33c |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.